Field
Embodiments described herein relate generally to calibrating and correcting projection data, and more specifically to matching the offset angle of the object projection data with the offset angle of calibration data, and then performing corrections to the object projection data using the calibration data.
Description of the Related Art
Computed tomography (CT) systems and methods are widely used, particularly for medical imaging and diagnosis. CT systems generally create images of one or more sectional slices through a subject's body. A radiation source, such as an X-ray source, irradiates the body from one side. A collimator, generally adjacent to the X-ray source, limits the angular extent of the X-ray beam, so that radiation impinging on the body is substantially confined to a planar region defining a cross-sectional slice of the body. At least one detector (and generally many more than one detector) on the opposite side of the body receives radiation transmitted through the body substantially in the plane of the slice. The attenuation of the radiation that has passed through the body is measured by processing electrical signals received from the detector.
FIG. 1A shows a CT sinogram, which is a plot of attenuation through the body as a function of “space” along a detector array (horizontal) and “time/angle” of a scan of measurements performed at a series of projection angles (vertical). The space dimension refers to the position along a one-dimensional array of X-ray detectors. The time/angle dimension refers to the projection angle of X-rays changing as a function of time, such that as time progresses the projection angle increments and projection measurements are performed at a linear succession of projection angles. The attenuation resulting from a particular volume (e.g., a vertebra) will trace out a sine wave around the vertical axis—volumes farther from the axis of rotation having sine waves with larger amplitudes, the phase of a sine wave determining the volume's angular position around the rotation axis. Performing an inverse Radon transform or equivalent image reconstruction method reconstructs an image from the projection data in the sinogram—the reconstructed image corresponding to a cross-sectional slice of the body, as shown in FIG. 1A.
Conventionally, energy-integrating detectors have been used to measure CT projection data. Now, recent technological developments are making photon-counting detectors a feasible alternative to conventional energy-integrating detectors. Photon-counting detectors have many advantages, including their capacity for performing spectral CT. To obtain the spectral nature of the transmitted X-ray data, the photon-counting detectors split the X-ray beam into its component energies or spectrum bins and count a number of photons in each of the bins. Since spectral CT involves the detection of transmitted X-rays at two or more energy levels, spectral CT generally includes dual-energy CT by definition.
Many clinical applications can benefit from spectral CT technology, which can provide improvement in material differentiation and beam hardening correction. Further, semiconductor-based photon-counting detectors are a promising candidate for spectral CT, which is capable of providing better spectral information compared with conventional spectral CT technology (e.g., dual-source, kVp-switching, etc.).
One advantage of spectral CT, and spectral X-ray imaging in general, is that materials having atoms with different atomic number Z also have different spectral profiles for attenuation. Thus, by measuring the attenuation at multiple X-ray energies, materials can be distinguished and the attenuation can be attributed to a particular atom (i.e., effective Z). This attribution enables spectral projection data to be mapped from the spectral domain to the material domain using a material decomposition. In some instances, this material decomposition is performed using a dual-energy analysis method.
The dual-energy analysis method can be used because the attenuation of X-rays in biological materials is dominated by two physical processes (i.e., photoelectric scattering and Compton scattering). Thus, the attenuation coefficient as a function of energy can be approximated by the decompositionμ(E,x,y)=μPE(E,x,y)+μC(E,x,y),wherein μPE(E, x, y) is the photoelectric attenuation and μC(E, x, y) is the Compton attenuation. This attenuation coefficient can be rearranged instead into a decomposition of a high-Z material (i.e., material 1) and a low-Z material (i.e., material 2) to becomeμ(E,x,y)≈μ1(E)c1(x,y)+μ2(E)c2(x,y),wherein c1,2(x,y) is a spatial function describing how much the imaged object located at position (x,y) is represented by material 1 and material 2, respectively.
In some CT systems, including those having topologies with a ring of photon-counting detectors inside the circular path of the X-ray source, measurement artifacts will be calibrated out using calibration scans similar to the object scans that collect projection data of the image object. For best results, any angular offset between the calibration scans and the object scans should be corrected. Correcting the angular offset will improve image quality of the reconstructed image. The angular offset between the calibration scans and the object scans can be described as a difference between the sub-view angular offset of the calibration projection data and the sub-view angular offset of the object projection data. The “sub-view angular offset” of projection data—where “projection data” refers to a collection of projection measurements for a series of projection angles—is defined for a given scan as the average offset angle between the actual projection angles and the nominal projection angle recorded using the data acquisition and motion control systems of the CT scanner. This difference between actual and nominal angles can arise from the tolerance limitations in real-world measurement systems (e.g., backlash in the gears and resolution limitations of the measurement encoders).
Generally, the sub-view angular offset will be different for different scans, where “different scans” includes that the rotation of the CT system is stopped and restarted between scans. Because the calibration projection data will likely have a different sub-view angular offset than the object projection data, without correcting for the differences in sub-view angular offset residual measurement artifacts remain after calibration corrections, resulting in poorer image quality for reconstructed images. On the other hand, a method that matches sub-view angular offset of the object projection data and calibration projection data results in better cancellation of measurement artifacts in the calibration corrected projection data and improved image quality for reconstructed images from the corrected projection data.